NCT05655117

Brief Summary

The goal of this pragmatic trial is to test the benefit of using artificial intelligence-based eye screening i.e, a fundus camera device in the early detection of eye complications in diabetics. The main questions it aims to answer are: To what extent does the application of artificial intelligence-based eye care at primary care clinics work well in achieving early detection of eye complications such as macular oedema? To what extent does the application of artificial intelligence-based eye care at primary care clinics work well in achieving early detection of eye complications such as retinopathy? Participants will be asked to participate in the screening for eye complications at primary care centres, and a fundus camera will be used for screening. Researchers will compare the proportion of detected cases with early signs of eye complication among those using artificial intelligence-based eye screening i.e., fundus camera, to the proportion of detected cases among those using routine eye care clinics at the primary care centre. Early detection of eye complications in diabetics prevents the risk of blindness.

Trial Health

35
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
440

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Jan 2023

Shorter than P25 for not_applicable

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

December 7, 2022

Completed
12 days until next milestone

First Posted

Study publicly available on registry

December 19, 2022

Completed
13 days until next milestone

Study Start

First participant enrolled

January 1, 2023

Completed
5 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 1, 2023

Completed
1 month until next milestone

Study Completion

Last participant's last visit for all outcomes

July 1, 2023

Completed
Last Updated

December 29, 2022

Status Verified

December 1, 2022

Enrollment Period

5 months

First QC Date

December 7, 2022

Last Update Submit

December 27, 2022

Conditions

Artificial IntelegenceDiabetic Retinopathy Associated With Type 2 Diabetes MellitusMacular Edema Due to Type 2 Diabetes Mellitus

Keywords

AI Eye Screening in diabeticsDiabetic retinopathymacular oedema

Outcome Measures

Primary Outcomes (2)

  • The detection rate of diabetic retinopathy in the intervention group vs. control group

    The proportion of the detected cases of diabetic retinopathy in the intervention group vs. control group

    6 month from the start of the study

  • The detection rate of macular oedema in the intervention group vs. control group.

    The proportion of the individuals who screened positive for macular oedema in the intervention group vs. control group.

    6 month from the start of the study

Secondary Outcomes (2)

  • The screening rate for retinopathy

    6 months after the start of the study

  • The screening rate for macular odema

    6 months after the start of the study

Study Arms (2)

AI-based screening for early detection of diabetic retinopathy and macular Oedema

EXPERIMENTAL

The application of AI devices i.e Fundus Camera to detect diabetic retinopathy and macular Oedema in diabetics at the primary care centre

Other: AI based eye screening

Routine screening for diabetic retinopathy and macular oedema

NO INTERVENTION

The Routine screening for diabetic retinopathy and macular oedema in diabetics during a routine visit to an eye care clinic at the primary care centre.

Interventions

AI based eye screeningOTHER

The application of AI devices i.e Fundus Camera to detect diabetic retinopathy and macular Oedema in diabetics at the primary care centre

AI-based screening for early detection of diabetic retinopathy and macular Oedema

Eligibility Criteria

Age18 Years - 90 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Diabetic patients aged 18-90

You may not qualify if:

  • Severely ill patient or patient with cancer

Contact the study team to confirm eligibility.

Sponsors & Collaborators

MeSH Terms

Conditions

Diabetic RetinopathyMacular Edema

Condition Hierarchy (Ancestors)

Retinal DiseasesEye DiseasesDiabetic AngiopathiesVascular DiseasesCardiovascular DiseasesDiabetes ComplicationsDiabetes MellitusEndocrine System DiseasesMacular DegenerationRetinal Degeneration

Study Officials

  • Khalil Alshammari, VIP Chief MO

    Hail Health Cluster

    STUDY CHAIR

  • Fakhralddin Elfakki, Researcher at MOC

    New Model of Care, Hail Health Cluser

    PRINCIPAL INVESTIGATOR

  • Meshari Aljamani, MOC Lead

    New Model of Care, Hail Health Cluster

    STUDY DIRECTOR

Central Study Contacts

Fakhralddin Elfakki, Researcher at MOC

CONTACT

+966530855161abbasfakhraddin@gmail.com

Marwa Mahmoud Mahdy, CSoC Lead

CONTACT

+966508258235maroo_79@hotmail.com

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
SCREENING
Intervention Model
PARALLEL
Sponsor Type
OTHER GOV
Responsible Party
SPONSOR

Study Record Dates

First Submitted

December 7, 2022

First Posted

December 19, 2022

Study Start

January 1, 2023

Primary Completion

June 1, 2023

Study Completion

July 1, 2023

Last Updated

December 29, 2022

Record last verified: 2022-12

Data Sharing

IPD Sharing
Will not share